PPTAgent — MCP Server by icip-cas

Last updated: 2026-04-28 · Indexed by AgentSkillsHub · Auto-synced every 8h

About PPTAgent

agent agentic-ai llm mcp openclaw presentation slide

Quick Facts

Stars	4,186
Forks	512
Language	Python
Category	MCP Server
License	MIT
Quality Score	54.052/100
Open Issues	7
Last Updated	2026-04-28
Created	2025-01-04
Platforms	mcp, python
Est. Tokens	~12797k

Compatible Skills

These tools work well together with PPTAgent for enhanced workflows:

octotools — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
PocketFlow — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)
ToolOrchestra — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
Hephaestus — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
RagaAI-Catalyst — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (50%)

PPTAgent alternative? Top 6 similar tools

Looking for a PPTAgent alternative? If you're comparing PPTAgent with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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Frequently Asked Questions

What is PPTAgent?

PPTAgent is An Agentic Framework for Reflective PowerPoint Generation. It is categorized as a MCP Server with 4.2k GitHub stars.

What programming language is PPTAgent written in?

PPTAgent is primarily written in Python. It covers topics such as agent, agentic-ai, llm.

How do I install or use PPTAgent?

You can find installation instructions and usage details in the PPTAgent GitHub repository at github.com/icip-cas/PPTAgent. The project has 4.2k stars and 512 forks, indicating an active community.

What license does PPTAgent use?

PPTAgent is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to PPTAgent?

The top alternatives to PPTAgent on Agent Skills Hub include casdoor, openagent, bytebot. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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